Conformational searching complications

Transition metal (TM) systems present a fundamental dilemma for computational chemists. On the one hand, TM centers are often associated with relatively complicated electronic structures which appear to demand some form of quantum mechanical (QM) approach (1). On the other hand, all forms of QM are relatively compute intensive and are impractical for conformational searching, virtual high-throughput screening, or dynamics simulations... 

The computational study of the osmium dihydroxylation of aliphatic al-kenes is much more complicated than the case of aromatic alkenes due to the large number of conformations that the former could adopt. To overcome this issue, we considered the system to be composed of two different parts the catalyst and the olefin. For the catalyst, the conformation considered is that from the X-ray structure. As already shown in the study of styrene [95], and in some experimental works [98], the catalyst is a fairly rigid molecule. For the aliphatic alkenes under study, there is a large number of possible conformations in addition, the stability of an olefin conformation is also affected by the interactions between the olefin substituent and the catalyst. Therefore, the catalyst must be included in the conformational search. The conformational analysis was done using a scheme based on the systematic search approach [99]. The strategy consisted of two parts first we developed a method to identify all of the possible conformations afterwards, we screened all of the possible conformations at MM level to select the most stable. Finally, we only carried out the relatively expensive QM/MM calculations on these selected conformations. 

Typically a simple scaling from binary to floating representation is used, but there are cases in which the real value is constrained to lie only in disconnected regions. This requires that a complicated filter be used. For instance, when doing conformational searches on proteins, the backbone Ramachandran plots. A conformational search will proceed more efficiently if the low-probability regions in the Ramachandran plot are never sampled. 

There are also hybrid methods which combine features from two or all three of the above. Opinions will freely be offered about which technique is best , but the reality is that different techniques will perform differently depending on the problem at hand. Except for very simple systems with only one or a few degrees of conformational freedom, systematic methods are not practical, and sampling techniques, which do not guarantee location of the lowest-energy structure (because they do not look everywhere), are the only viable alternative. By default, Spartan uses systematic searching for systems with only a few degrees of conformational freedom and Monte-Carlo methods for more complicated systems. 

NMR structure determination can be viewed as a global optimization problem for a target function in the conformational space to determine three-dimensional coordinates. The target function is normally a hybrid potential between the NMR-derived structural information and empirical steric conditions. The conformational space means the total degrees of freedom for the atomic positions, typically more than a thousand. The conformational space search for the highly complicated system has been a challenging computational target. 

Terazosin hydrochloride is a real challenge for crystal structure prediction because the cation is large and flexible and because its ionic nature complicates the calculation of the electrostatic contribution to the lattice energy. However, knowledge of the experimental crystal structures of four forms was used to deduce the most likely conformation of the cation as well as the protonation site and the most likely location of the chlorine anion. This neutral anion-cation complex was used as the search unit in the crystal structure prediction simulations. The known structures were also used to modify the standard Dreiding 2.21 force field in such a manner that it was able to reproduce the... 

Fabrication of an enzyme-modified electrode, and indeed any biosensor, requires stepwise selection and integration of a number of complex components. First, the redox enzyme chosen must have the required selectivity for the analyte as well as a product that is detectable at the signal transducer (in this case the electrode surface). A search of the literature reveals that a relatively small number of enzymes have been reported as functional on biosensors, and two classes of enzymes (oxido-reductase and dehydrogenase) predominate. Notably, the oxido-reductase family, and glucose oxidase in particular, account for the majority of all reports in the literature. Other factors that complicate the choice of enzyme include the necessity for a derivatization procedure that does not destroy the active site of the enzyme. In some cases, proper orientation of the enzyme s active site must also be considered. Glutamate dehydrogenase, a protein whose conformation (and therefore activity) is dependent on electrostatic forces, has been... 

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